Special Section on Image Processing for Cultural Heritage

Southeast Asian palm leaf manuscript images: a review of handwritten text line segmentation methods and new challenges

[+] Author Affiliations
Made Windu Antara Kesiman

University of La Rochelle, Laboratoire Informatique Image Interaction (L3i), Avenue Michel Crépeau 17042, La Rochelle Cedex 1, France

University of Pendidikan Ganesha, Laboratory of Cultural Informatics, Jalan Udayana No. 11, Singaraja, Bali, Indonesia

Dona Valy

Institute of Technology of Cambodia, Department of Information and Communication Engineering, Pochentong Boulevard, BP 86, Phnom Penh, Cambodia

Université Catholique de Louvain, Institute of Information and Communication Technologies, Electronic, and Applied Mathematics, Place du Levant 3, Louvain-la-Neuve 1348, Belgium

Jean-Christophe Burie, Jean-Marc Ogier

University of La Rochelle, Laboratoire Informatique Image Interaction (L3i), Avenue Michel Crépeau 17042, La Rochelle Cedex 1, France

Erick Paulus, Setiawan Hadi

University of Padjadjaran, Robotics, Artificial Intelligence, and Digital Image Laboratory, Jalan Raya Bandung Sumedang, KM 21, Jatinangor 45363, Indonesia

I. Made Gede Sunarya

University of Pendidikan Ganesha, Laboratory of Cultural Informatics, Jalan Udayana No. 11, Singaraja, Bali, Indonesia

Kim Heng Sok

Institute of Technology of Cambodia, Department of Information and Communication Engineering, Pochentong Boulevard, BP 86, Phnom Penh, Cambodia

J. Electron. Imaging. 26(1), 011011 (Nov 17, 2016). doi:10.1117/1.JEI.26.1.011011
History: Received July 1, 2016; Accepted October 26, 2016
Text Size: A A A

Abstract.  Due to their specific characteristics, palm leaf manuscripts provide new challenges for text line segmentation tasks in document analysis. We investigated the performance of six text line segmentation methods by conducting comparative experimental studies for the collection of palm leaf manuscript images. The image corpus used in this study comes from the sample images of palm leaf manuscripts of three different Southeast Asian scripts: Balinese script from Bali and Sundanese script from West Java, both from Indonesia, and Khmer script from Cambodia. For the experiments, four text line segmentation methods that work on binary images are tested: the adaptive partial projection line segmentation approach, the A* path planning approach, the shredding method, and our proposed energy function for shredding method. Two other methods that can be directly applied on grayscale images are also investigated: the adaptive local connectivity map method and the seam carving-based method. The evaluation criteria and tool provided by ICDAR2013 Handwriting Segmentation Contest were used in this experiment.

© 2016 SPIE and IS&T

Citation

Made Windu Antara Kesiman ; Dona Valy ; Jean-Christophe Burie ; Erick Paulus ; I. Made Gede Sunarya, et al.
"Southeast Asian palm leaf manuscript images: a review of handwritten text line segmentation methods and new challenges", J. Electron. Imaging. 26(1), 011011 (Nov 17, 2016). ; http://dx.doi.org/10.1117/1.JEI.26.1.011011


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